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The 'SAR Matrix' method and its extensions for applications in medicinal chemistry and chemogenomics.

Gupta-Ostermann D, Bajorath J - F1000Res (2014)

Bottom Line: The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets.It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces.The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, D-53113, Germany.

ABSTRACT
We describe the 'Structure-Activity Relationship (SAR) Matrix' (SARM) methodology that is based upon a special two-step application of the matched molecular pair (MMP) formalism. The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets. It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces. The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.

No MeSH data available.


Matrix overlap distribution.Shown is a histogram with the matrix overlap distribution for SARMs from an in-house focused library.
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f3: Matrix overlap distribution.Shown is a histogram with the matrix overlap distribution for SARMs from an in-house focused library.

Mentions: where,n_col correspond to the number of data set compounds present in each column. RO yields a numerical score between 0 (no overlap) and 1 (complete overlap).Figure 3 reports the matrix overlap distribution for SARMs from the focused library referred to above, which is a fairly representative distribution for structurally homogeneous data sets. Here 5% of the SARMs have an RO of 0 for each column; hence, the final matrix overlap score is 0 indicating the mutually exclusive nature of the substitution pattern among the A_MMS. By contrast, 30% of the SARMs have an RO of 1 for each column; hence, the final matrix overlap is 1 reflecting the presence of A_MMS with identical substitution patterns. As an alternative measure, “matrix coverage” (C), which accounts for the proportion of cells in a SARM that are populated with real compoundsn_matrix can be calculated as:


The 'SAR Matrix' method and its extensions for applications in medicinal chemistry and chemogenomics.

Gupta-Ostermann D, Bajorath J - F1000Res (2014)

Matrix overlap distribution.Shown is a histogram with the matrix overlap distribution for SARMs from an in-house focused library.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4215758&req=5

f3: Matrix overlap distribution.Shown is a histogram with the matrix overlap distribution for SARMs from an in-house focused library.
Mentions: where,n_col correspond to the number of data set compounds present in each column. RO yields a numerical score between 0 (no overlap) and 1 (complete overlap).Figure 3 reports the matrix overlap distribution for SARMs from the focused library referred to above, which is a fairly representative distribution for structurally homogeneous data sets. Here 5% of the SARMs have an RO of 0 for each column; hence, the final matrix overlap score is 0 indicating the mutually exclusive nature of the substitution pattern among the A_MMS. By contrast, 30% of the SARMs have an RO of 1 for each column; hence, the final matrix overlap is 1 reflecting the presence of A_MMS with identical substitution patterns. As an alternative measure, “matrix coverage” (C), which accounts for the proportion of cells in a SARM that are populated with real compoundsn_matrix can be calculated as:

Bottom Line: The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets.It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces.The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.

View Article: PubMed Central - PubMed

Affiliation: Department of Life Science Informatics, B-IT, LIMES Program Unit Chemical Biology and Medicinal Chemistry, Rheinische Friedrich-Wilhelms-Universität, Bonn, D-53113, Germany.

ABSTRACT
We describe the 'Structure-Activity Relationship (SAR) Matrix' (SARM) methodology that is based upon a special two-step application of the matched molecular pair (MMP) formalism. The SARM method has originally been designed for the extraction, organization, and visualization of compound series and associated SAR information from compound data sets. It has been further developed and adapted for other applications including compound design, activity prediction, library extension, and the navigation of multi-target activity spaces. The SARM approach and its extensions are presented here in context to introduce different types of applications and provide an example for the evolution of a computational methodology in pharmaceutical research.

No MeSH data available.